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Non-canonical ORFs nuORFdb Track Settings
 
ncORFs: nuORFdb - non-canonical ORFs from nuORFdb v1.2

Configure track container: Non-canonical Open Reading Frames

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Kozak consensus strength|Strong/Moderate/Weak per Kozak rule on -3 and +4 Simplified ORF category for display Start codon (ATG, CTG, GTG, TTG, ACG, other) read from genome ORF merge type (e.g. Pseudogene, lincRNA, 5' uORF)
Match if all one or more match
Match if all one or more match
Match if all one or more match
Match if all one or more match
Data schema/format description and download
Assembly: Human Dec. 2013 (GRCh38/hg38)
Data last updated at UCSC: 2026-05-19 11:39:36

Description

This track displays 229,251 non-canonical open reading frames (ORFs) from nuORFdb v1.2 (novel unannotated ORF database), a database of ORFs with evidence of translation detected by ribosome profiling (Ribo-seq). nuORFdb was developed at the Broad Institute of MIT and Harvard as a resource for identifying non-canonical peptides in immunopeptidomic mass spectrometry datasets.

The ORFs were predicted using a hierarchical pipeline that aggregates ribosome profiling signal across 29 primary healthy and cancer tissue samples and cell lines. The pipeline operates at multiple levels—individual samples, tissues, and combined across all samples—to predict lowly translated ORFs while maintaining sensitivity for tissue-specific variants. All ORFs have a minimum length of 8 amino acids.

Display Conventions and Configuration

Items are displayed in bigGenePred format. Each item is labeled with the nuORFdb ORF identifier, which encodes the source Ensembl transcript and ORF number (e.g. ENST00000488147.1_1_1). Color reflects the categorical Kozak consensus strength:

Strong – A/G at position −3 and G at position +4
Moderate – only one of those positions matches
Weak – neither position matches
non-ATG – near-cognate start codon; the Kozak rule does not apply
no context – chromosome edge or context unavailable

Mouseover shows the ORF ID in its host gene, gene biotype, start codon, Kozak strength and TE, predictor type, and the simplified plotType category.

Available filters: start codon, Kozak strength, Kozak TE, ORF category (plotType: 8 broad classes; or type: 25 finer categories).

The track includes the following ORF categories (by type):

  • Out-of-Frame – ORFs overlapping a CDS but in a different reading frame (57,713)
  • 5' uORF – upstream ORFs in the 5' UTR (32,595)
  • 3' dORF – downstream ORFs in the 3' UTR (30,656)
  • lincRNA – ORFs in long intergenic non-coding RNAs (20,399)
  • 5' Overlap uORF – upstream ORFs overlapping the main CDS (20,119)
  • ncRNA Retained Intron – ORFs in retained-intron transcripts (19,259)
  • 3' Overlap dORF – downstream ORFs overlapping the main CDS (18,028)
  • ncRNA Processed Transcript – ORFs in processed transcripts (14,173)
  • Pseudogene – ORFs in pseudogenes (7,727)
  • Antisense – ORFs in antisense transcripts (6,300)
  • and other minor categories

Each item also includes the predicted protein sequence and additional classification fields (predictorType, plotType, geneType) from the nuORFdb annotations.

Data Access

The raw data can be explored interactively with the Table Browser or the Data Integrator. The data can be accessed from scripts through our API; the track name is "nuorfdb".

For automated download and analysis, the genome annotation is stored in a bigBed file that can be downloaded from our download server. Individual regions or the whole genome annotation can be obtained using our tool bigBedToBed, which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tool can also be used to obtain only features within a given range, e.g.

bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/ncOrfs/nuorfdb/nuorfdb.kozak.bb -chrom=chr21 -start=0 -end=100000000 stdout

The original data files can be downloaded from the nuORFdb website at the Broad Institute.

Methods

The nuORFdb v1.2 data files (BED12 coordinates, Excel annotations, and protein FASTA sequences) were downloaded from the Broad Institute. The BED12 file was combined with the annotation spreadsheet (keyed on ORF_ID_hg38) and protein FASTA (keyed on sequence header ID) to produce a bigGenePred+ format file with 23 fields (12 standard BED fields, 8 bigGenePred fields, and 3 extended fields: predictorType, plotType, and proteinSequence).

A small number of entries (176 out of 229,251) used non-standard chromosome names (e.g. chrGL000008.2, chrMT) which were mapped to UCSC standard names (e.g. chr4_GL000008v2_random, chrM).

Credits

Thanks to Tamara Ouspenskaia, Travis Law, Karl Clauser, and colleagues at the Broad Institute of MIT and Harvard for creating nuORFdb and making the data publicly available. Thanks to Eric Malekos, UCSC, for suggesting this database.

References

Ouspenskaia T, Law T, Clauser KR, Klaeger S, Sarkizova S, Aguet F, Li B, Christian E, Knisbacher BA, Le PM et al. Unannotated proteins expand the MHC-I-restricted immunopeptidome in cancer. Nat Biotechnol. 2022 Feb;40(2):209-217. DOI: 10.1038/s41587-021-01021-3; PMID: 34663921; PMC: PMC10198624